1. Field of the Invention
The present invention relates to a method, an apparatus, and a program for detecting faces from within target images.
2. Description of the Related Art
Correction of skin tones in snapshots photographed with digital cameras by investigating color distributions within facial regions, and recognition of people who are pictured in digital images obtained by digital video cameras of security systems is being performed. In these cases, it is necessary to detect regions (facial regions) within digital images that correspond to people's faces. For this reason, various techniques for detecting faces from within digital images have been proposed.
An example of such a technique is one in which partial images are cut out at a plurality of different positions from within a detection target image. Judgment is performed regarding whether the partial images are facial images that represent faces, thereby detecting faces within the detection target image. Template matching techniques or techniques employing classifier modules, which have learned characteristics of faces by a machine learning method, may be employed to judge whether the partial images represent faces (refer to, for example, S. Lao et al., “Fast Omni-Directional Face Detection”, Meeting on Image Recognition and Understanding, pp. II271-II276, July 2004, and U.S. Patent Application Publication No. 20050100195).
The positions and inclinations of faces that appear in digital images (hereinafter, simply referred to as “inclinations”) are often indeterminate, excluding cases such as ID photos, for which photography conditions are substantially uniform. Meanwhile, brightness distributions that represent characteristics of faces within digital images change when the inclinations thereof change. Therefore, it is difficult to detect a plurality of faces having different inclinations with a single detection process. Accordingly, detection processes are generally repeated while varying the inclinations of faces to be detected in order to detect faces, of which the inclinations are unknown.
There are cases in which it is not necessary to detect faces having all possible inclinations. An example is a case in which only a single face needs to be detected from within detection target images. Another example is a case in which faces are to be detected from within a plurality of images which have been obtained by continuous imaging, wherein if a face is detected in one of the images, detection of faces in the other images can be accomplished by fixing the inclination to that of the detected face. In these cases, the amount of processing necessary to achieve the objective of the detection process is influenced by the order of priority assigned to inclinations of faces to be detected.
However, in conventional techniques, the order of inclinations of faces to be detected is set in advance, and there has been no particular effort to reduce the amount of processing during face detection.